SOCIAL NETWORK ANALYSIS UNTUK MENGIDENTIFIKASI AKUN KUNCI DALAM PERCAKAPAN CAPRES DI TWITTER

Fatkhul, Amin and Imam Husni, Al Amin and Edy, Winarno and Setyawan, Wibisono and Taufiq, Dwicahyono SOCIAL NETWORK ANALYSIS UNTUK MENGIDENTIFIKASI AKUN KUNCI DALAM PERCAKAPAN CAPRES DI TWITTER. JURNAL TEKNOINFO Volume 18, Nomor 2, Juli 2024, Page 316-329.

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Abstract

This study aims to explore conversations about presidential candidates on Twitter (X) using social network analysis (SNA). The analysis methods include Degree Centrality, Betweenness Centrality, and Closeness Centrality to identify central accounts in discussions about specific presidential candidates. Twitter (X) datasets were processed and analyzed using SNA tools. Network visualizations were conducted using Gephi 0.10.1 to understand the interaction structures among accounts. In a case study focusing on the "Anies Muhaimin" pair, the analysis revealed that accounts such as @kba_news and @PeraWat81282560 exhibited high Degree Centrality, indicating significant involvement in disseminating information and maintaining direct connections with other accounts in the network. Meanwhile, for keywords "Ganjar Mahfud" and "Prabowo Gibran," dominant accounts were found to play crucial roles in coordinating and influencing conversations. Implications of these findings highlight how social network structures influence the spread of political information on social media. The study provides insights into the dynamics of interactions among accounts in the context of presidential election campaigns and underscores the importance of understanding the influence of central accounts on public opinion. In conclusion, Twitter (X) social network analysis offers a profound understanding of how political information spreads and is influenced within conversations about presidential candidates. These findings are relevant for political campaign strategies and reputation management in the digital era.

Item Type:	Article
Subjects:	Q Science > Q Science (General)
Faculty / Institution:	Fakultas Teknologi Informasi
Depositing User:	Fakultas Ekonomi
Date Deposited:	23 Apr 2025 06:20
Last Modified:	23 Apr 2025 06:20
URI:	https://eprints.unisbank.ac.id/id/eprint/10239

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